Hi all.

I want to insert my dataframe into InterSystems IRIS. So, I tried to do this:

df = spark.read.load("/home/imported-openssh-key/zeppelin-0.8.0-bin-all/bin/resultData3/DF.json", format="json")
df.write.format("com.intersystems.spark").\
option("url", "IRIS://localhost:51773/DEDUPL").\
option("user", "********").option("password", "********").\
option("dbtable", "try.test1").save()

And got this error:

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We’re now less than a month away from our annual conference, the InterSystems Global Summit. This year, we’ll be descending on the beautiful outskirts of San Antonio, a city worth visiting for its wonderful river walkway and its 18th century Spanish Mission, even if it hadn’t been the location of this year’s InterSystems event. Leaving the tourist guidance to the tourist guides, let’s take a closer look at what the conference has in stock for you, including a dedicated post-summit symposium on AI and ML on Wednesday October 3!

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Hi Everyone!

Very soon, almost every product and application will include artificial intelligence (AI).

On the afternoon of Wednesday, October 3, at the Global Summit 2018  in San Antonio we’re pulling together experts from InterSystems and from the front lines of the AI industry to discuss the current and future state-of-the-art for AI solutions. 

Learn more about our Post-Summit Symposium: Artificial Intelligence and Machine Learning.

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The recording of Anton Umnikov's It's Machine Learning, Not Rocket Science! webinar is now available on learning.intersystems.com

In it, Anton provides a great, high-level introduction to machine learning and shows why you don't need to be a "unicorn" data scientist to start using machine learning to your advantage! 

Watch it now

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With the release of InterSystems IRIS, we're also making available a nifty bit of software that allows you to get the best out of your InterSystems IRIS cluster when working with Apache Spark for data processing, machine learning and other data-heavy fun. Let's take a closer look at how we're making your life as a Data Scientist easier, as you're probably already facing tough big data challenges already, just from the influx of job offers in your inbox!

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Apache Spark has rapidly become one of the most exciting technologies for big data analytics and machine learning. Spark is a general data processing engine created for use in clustered computing environments. Its heart is the Resilient Distributed Dataset (RDD) which represents a distributed, fault tolerant, collection of data that can be operated on in parallel across the nodes of a cluster. Spark is implemented using a combination of Java and Scala and so comes as a library that can run on any JVM.

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For the engaging eXPerience Labs (XP-Labs) training sessions, my first customer and favourite department (Learning Services), was working hard assisting and supporting us all behind the scene.

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